The term "dark citations," which has been previously used to refer to citations of information products outside of traditional peer-reviewed journal articles, is adapted here to refer to those that are not linked to a known indexed identifier and are effectively invisible to traditional bibliometric analysis. We investigate an unexplored source of citations in the biomedical and public health literature by surveying the extent of dark citations across the U.S. government. We systematically focus on public health, quantify their occurrences across the government, and provide a comprehensive dataset for all dark citations within PubMed.

The term "dark citations", which has been previously used to refer to citations of information products outside of traditional peer-reviewed journal articles, is adapted here to refer to those that are not linked to a known indexed identifier and are effectively invisible to traditional bibliometric analysis. We investigate an unexplored source of citations in the biomedical and public health literature by surveying the extent of dark citations across the U.S. government. We systematically focus on public health, quantify their occurrences across the government, and provide a comprehensive dataset for all dark citations within PubMed. Copyright The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. This article is a US Government work. It is not subject to copyright under 17 USC 105 and is also made available for use under a CC0 license.

Importance: It is uncertain to what extent established cardiovascular risk factors are associated with venous thromboembolism (VTE). Objective: To estimate the associations of major cardiovascular risk factors with VTE, ie, deep vein thrombosis and pulmonary embolism. Design, Setting, and Participants: This study included individual participant data mostly from essentially population-based cohort studies from the Emerging Risk Factors Collaboration (ERFC; 731728 participants; 75 cohorts; years of baseline surveys, February 1960 to June 2008; latest date of follow-up, December 2015) and the UK Biobank (421537 participants; years of baseline surveys, March 2006 to September 2010; latest date of follow-up, February 2016). Participants without cardiovascular disease at baseline were included. Data were analyzed from June 2017 to September 2018. Exposures: A panel of several established cardiovascular risk factors. Main Outcomes and Measures: Hazard ratios (HRs) per 1-SD higher usual risk factor levels (or presence/absence). Incident fatal outcomes in ERFC (VTE, 1041; coronary heart disease [CHD], 25131) and incident fatal/nonfatal outcomes in UK Biobank (VTE, 2321; CHD, 3385). Hazard ratios were adjusted for age, sex, smoking status, diabetes, and body mass index (BMI). Results: Of the 731728 participants from the ERFC, 403396 (55.1%) were female, and the mean (SD) age at the time of the survey was 51.9 (9.0) years; of the 421537 participants from the UK Biobank, 233699 (55.4%) were female, and the mean (SD) age at the time of the survey was 56.4 (8.1) years. Risk factors for VTE included older age (ERFC: HR per decade, 2.67; 95% CI, 2.45-2.91; UK Biobank: HR, 1.81; 95% CI, 1.71-1.92), current smoking (ERFC: HR, 1.38; 95% CI, 1.20-1.58; UK Biobank: HR, 1.23; 95% CI, 1.08-1.40), and BMI (ERFC: HR per 1-SD higher BMI, 1.43; 95% CI, 1.35-1.50; UK Biobank: HR, 1.37; 95% CI, 1.32-1.41). For these factors, there were similar HRs for pulmonary embolism and deep vein thrombosis in UK Biobank (except adiposity was more strongly associated with pulmonary embolism) and similar HRs for unprovoked vs provoked VTE. Apart from adiposity, these risk factors were less strongly associated with VTE than CHD. There were inconsistent associations of VTEs with diabetes and blood pressure across ERFC and UK Biobank, and there was limited ability to study lipid and inflammation markers. Conclusions and Relevance: Older age, smoking, and adiposity were consistently associated with higher VTE risk.

AIMS: To determine (1) the prevalence of SubD states among adults with diabetes, and (2) whether evidence exists of an independent association between diabetes status and SubD, controlling for selected confounders. METHODS: Data from the 2007-2012 National Health and Nutrition Examination Surveys were combined to estimates of depressive states by diabetes status among the noninstitutionalized U.S. adult population, and to assess the association of diabetes status and depressive states using a polytomous logistic regression model. RESULTS: An estimated 17%, or 3.7 million, of U.S. adults with diabetes (diagnosed and undiagnosed) met criteria for either mD or ssD. The majority of SubD cases with diabetes were found to be ssD (10.1%) compared with mD (6.9%). After controlling for the effects of age, sex, race and ethnicity, education, body mass index, and poverty as covariates, an independent association persists between diagnosed diabetes and each SubD grouping (ssD: OR=1.82, CIs 1.33, 2.47; mD: OR=1.95, CIs 1.39, 2.74) compared with respondents having no diabetes. No association was found between depression and undiagnosed diabetes or prediabetes compared with those having no diabetes. CONCLUSION: Milder forms of depression such as ssD and mD are more extant than major depressive episodes among adults with diabetes. The odds that an adult with diagnosed diabetes meets the criteria for ssD or mD are higher by 80% and 95%, respectively, after controlling for age, sex, race and ethnicity, education, body mass index, and poverty factors when compared against adults with no diabetes.